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Economics Data Science Jobs (NOW HIRING)

This position will report to the Head of Data Science and Geospatial Analytics. The ideal candidate is a practitioner who thinks first like an economist, real estate analyst, or quantitative urban ...

Completed master's or other advanced degree in an analytical field such as statistics, mathematics, economics, data science, quantitative marketing, operations research, industrial engineering, etc.

Completed master's or other advanced degree in an analytical field such as statistics, mathematics, economics, data science, quantitative marketing, operations research, industrial engineering, etc.

Completed master's or other advanced degree in an analytical field such as statistics, mathematics, economics, data science, quantitative marketing, operations research, industrial engineering, etc.

Completed master's or other advanced degree in an analytical field such as statistics, mathematics, economics, data science, quantitative marketing, operations research, industrial engineering, etc.

Completed master's or other advanced degree in an analytical field such as statistics, mathematics, economics, data science, quantitative marketing, operations research, industrial engineering, etc.

Completed Masters or other advanced degrees, in an analytical field such as statistics, mathematics, economics, data science, quantitative marketing, operations research, industrial engineering, etc.

Completed Masters or other advanced degrees, in an analytical field such as statistics, mathematics, economics, data science, quantitative marketing, operations research, industrial engineering, etc.

Completed Masters or other advanced degrees, in an analytical field such as statistics, mathematics, economics, data science, quantitative marketing, operations research, industrial engineering, etc.

Completed Masters or other advanced degrees, in an analytical field such as statistics, mathematics, economics, data science, quantitative marketing, operations research, industrial engineering, etc.

Completed Masters or other advanced degrees, in an analytical field such as statistics, mathematics, economics, data science, quantitative marketing, operations research, industrial engineering, etc.

Completed Masters or other advanced degrees, in an analytical field such as statistics, mathematics, economics, data science, quantitative marketing, operations research, industrial engineering, etc.

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Showing results 1-20

Economics Data Science information

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$41.5K

$142.5K

$201K

How much do economics data science jobs pay per year?

As of Jul 11, 2026, the average yearly pay for economics data science in the United States is $142,460.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,500.00 and $166,500.00 per year, depending on experience, location, and employer.

Can economics majors work in data science?

Economics majors can work in data science roles, as their training in economic theory, statistical analysis, and quantitative methods provides a strong foundation. Success often depends on acquiring skills in programming languages like Python or R, data manipulation, and machine learning tools. Many data science positions value interdisciplinary knowledge, making economics a relevant background for analyzing and interpreting complex data sets.

What are common projects or responsibilities for professionals in Economics Data Science roles?

Economics Data Science professionals often work on projects that involve economic modeling, market analysis, and forecasting trends using large datasets. Typical responsibilities include gathering and cleaning economic data, developing predictive models, conducting statistical analyses, and translating results into actionable recommendations for business strategy or policy decisions. You may collaborate closely with economists, business analysts, and decision-makers to inform company direction or solve complex real-world problems. This role often involves a mix of independent data exploration and teamwork, offering opportunities to drive impactful results and shape organizational strategy.

What is economics data science?

Economics data science is a field that combines economic theory with data analysis and statistical methods to understand and solve economic problems. Professionals in this area use tools like Python, R, and econometrics to analyze large datasets, forecast trends, and inform policy or business decisions.

What are the key skills and qualifications needed to thrive in the Economics Data Science position, and why are they important?

To thrive in Economics Data Science, you need a strong background in economics, statistics, and programming (especially Python or R), often backed by a degree in economics, data science, or a related field. Proficiency with data analysis tools such as SQL, machine learning frameworks, and visualization software like Tableau is commonly required, and certifications in data science or analytics are advantageous. Excellent problem-solving abilities, communication skills, and a collaborative mindset help distinguish top performers in this position. These skills are crucial for effectively analyzing economic data, generating actionable insights, and conveying complex findings to both technical and non-technical stakeholders.

Is 40 too late for data science?

Economics Data Science is a field that values skills and experience over age; many professionals transition into data science later in their careers. Gaining proficiency in programming languages like Python or R, along with statistical knowledge, can facilitate entry regardless of age, and continuous learning is common in the industry.

What jobs can I get with data science and economics?

With a background in data science and economics, you can pursue roles such as economic analyst, data scientist, financial analyst, policy analyst, or market researcher. These positions often require skills in statistical analysis, programming (e.g., Python, R), and understanding economic principles to analyze data and inform decision-making.

What is an Economics Data Science job?

An Economics Data Science job combines economic theory, statistical analysis, and machine learning to interpret complex data and inform decision-making. Professionals in this field work with large datasets to analyze market trends, forecast economic conditions, and optimize business strategies. They commonly use programming languages like Python or R and tools such as SQL and econometric models. This role is valuable in industries like finance, government, and tech, where data-driven economic insights are crucial.

More about Economics Data Science jobs
What cities are hiring for Economics Data Science jobs? Cities with the most Economics Data Science job openings:
What are the most commonly searched types of Economics Data Science jobs? The most popular types of Economics Data Science jobs are:
What states have the most Economics Data Science jobs? States with the most job openings for Economics Data Science jobs include:
Infographic showing various Economics Data Science job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Remote job distribution, with an average salary of $142,460 per year, or $68.5 per hour.
Junior Data Scientist

Junior Data Scientist

Cushman & Wakefield

Chicago, IL • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 17 days ago


Cushman & Wakefield rating

7.5

Company rating: 7.5 out of 10

Based on 153 frontline employees who took The Breakroom Quiz

76th of 160 rated real estate companies


Job description

Job Title
Junior Data Scientist
Job Description Summary
This role sits at the intersection of real estate economics, urban analysis, and data science. The Junior Data Scientist will support the development and evolution of Cushman and Wakefield Quantitative Insight Group's (QIG) analytical capabilities by producing rigorous, insight-driven work on commercial real estate markets across the Americas. This position will report to the Head of Data Science and Geospatial Analytics. The ideal candidate is a practitioner who thinks first like an economist, real estate analyst, or quantitative urban planner, and who brings the technical skills to build and operate the data infrastructure their own work requires.
This is not primarily an engineering role, though the ideal candidate will possess data engineering knowledge, skills, and abilities. The Analyst will spend most of their time doing substantive analytical and research work: synthesizing complex datasets, identifying market patterns and anomalies, and producing outputs that inform Cushman & Wakefield's House View, including elements that are unique to QIG, and related analytical products for key clients. At the same time, the candidate should be comfortable constructing and maintaining data pipelines, working fluently in Python and/or R and SQL, and collaborating closely with Technology & Data Solutions (TDS) as a knowledgeable and credible partner.
Job Description
Key Responsibilities
Real Estate & Urban Economic Analysis (45%)
  • Conduct rigorous quantitative analysis on commercial real estate markets, synthesizing property, macroeconomic, and urban data to surface market trends, structural shifts, and investment-relevant insights.

  • Apply econometric and statistical methods (time series modeling, regression, spatial econometrics, or similar) to real estate and labor market questions in support of QIG research products.

  • Integrate geospatial data and methods into analytical workflows: working with Census geographies, parcel data, land use classifications, walkability or transit metrics, demographic overlays, and similar inputs to enrich market analysis.

  • Contribute to the development of novel datasets and indicators that advance QIG's analytical edge, including working closely with the Head of Data Science & Geospatial Analytics to specify and build integrated data products combining proprietary CRE data with public and third-party sources.

  • Support the QIG team on ad hoc analytical requests from Americas Research, the Global Think Tank, and senior stakeholders, producing clean, well-documented, and reproducible outputs.

Data Engineering & Pipeline Maintenance (35%)
  • Build and maintain automated data pipelines for ingesting, transforming, and storing CRE and macroeconomic datasets used in analytical models and reoccurring analysis.

  • Ensure data integrity and consistency across QIG inputs and outputs through validation, quality control procedures, and structured data interfaces.

  • Perform exploratory data analysis and profiling on raw and processed datasets to validate pipeline outputs and identify anomalies or inconsistencies.

  • Partner with PRI (Property Research & Intelligence), TDS (Technology & Data Solutions), and the GIS team to ensure governance of time series and geospatial data, particularly as geography-based competitive sets evolve.

  • Serve as a knowledgeable liaison to TDS: translating analytical requirements into engineering specifications, tracking the status of data requests in the TDS backlog, and validating outputs against analytical expectations.

Documentation, Integration & Infrastructure (20%)
  • Develop and maintain internal documentation covering data sources, model architecture, data flows, and diagnostic procedures, with attention to field-level lineage and traceability.

  • Serve as the team's subject matter expert on integration and processing of internal, third-party vendor, and public datasets (e.g., Census TIGER, IPUMS, LODES, NLCD, Overture Maps), and advise on cleaning, normalization, and appropriate analytical applications.

  • Monitor the evolution of third-party data products; assess their fit against QIG analytical requirements and produce intake specifications when new sources are approved for integration.

  • Support the adoption of emerging analytical technologies (including ML/AI methods and advanced data infrastructure patterns) through hands-on prototyping and coordination with TDS where appropriate.

Qualifications
  • Bachelor's degree in Economics, Data Science, Real Estate, Applied Economics, Geography, Urban Planning or any closely related field with quantitative emphasis. A master's degree is preferred and a doctoral degree is a plus.

  • 2 to 6 years of experience in a research, analytical, or data science role, preferably in a real estate, urban policy, planning, or economic research context.

  • Strong command of quantitative methods: regression, time series analysis, spatial econometrics, or comparable approaches applied to real estate or urban economic questions.

  • Working knowledge of geospatial data and methods: experience with GIS tools (ArcGIS, QGIS, or programmatic approaches via R or Python), familiarity with spatial data formats and concepts, and comfort integrating geographic context into analysis.

  • Proficiency in Python and/or R for data analysis, modeling, and pipeline construction; working knowledge of SQL. Familiarity with cloud platforms (Azure, AWS) and version control is a plus.

  • Experience working with public datasets commonly used in urban and real estate research: Census products (ACS, TIGER, LODES), BLS, IPUMS, or similar.

  • Ability to produce clean, well-documented, reproducible analytical work and communicate findings clearly to both technical and non-technical audiences.

  • Comfortable operating in a cross-functional environment, working both independently and alongside engineering and research teams on iterative deliverables.

  • Genuine intellectual interest in urban economics, commercial real estate markets, and the spatial dimensions of economic activity.

  • Comfortability in communicating analysis, methods and related topics with related teams and immediate management.

Cushman & Wakefield also provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health, vision, and dental insurance, flexible spending accounts, health savings accounts, retirement savings plans, life, and disability insurance programs, and paid and unpaid time away from work. In addition to a comprehensive benefits package, Cushman and Wakefield provide eligible employees with competitive pay, which may vary depending on eligibility factors such as geographic location, date of hire, total hours worked, job type, business line, and applicability of collective bargaining agreements.
The compensation that will be offered to the successful candidate will depend on factors such as whether the position is covered by a collective bargaining agreement, the geographic area in which the work will be performed, market pay rates in that area, and the candidate's experience and qualifications.
The company will not pay less than minimum wage for this role.
The compensation for the position is: $ 114,750.00 - $135,000.00
Cushman & Wakefield is an Equal Opportunity employer to all protected groups, including protected veterans and individuals with disabilities. Discrimination of any type will not be tolerated.
In compliance with the Americans with Disabilities Act Amendments Act (ADAAA), if you have a disability and would like to request an accommodation in order to apply for a position at Cushman & Wakefield, please call the ADA line at 1-888-365-5406 or email Accommodations@cushwake.com. Please refer to the job title and job location when you contact us.
INCO: "Cushman & Wakefield"

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